Chapter: Introduction to Human Nutrition: Body Composition

Bioelectrical impedance - Body composition techniques

In bioelectrical impedance, a small alternating current is applied to the body.

Bioelectrical impedance

In bioelectrical impedance, a small alternating current is applied to the body. It is assumed that the body consists of different components, of which water and dissolved electrolytes are able to conduct the current. Hence, body impedance is a measure of body water. The electrical resistance or impedance of an electro-lyte solution depends on several factors, of which the most important are the amount of electrolytes (pure water does not conduct the current), the kind of electrolytes, and the temperature of the solution. If currents of low frequency (<5 kHz) are used, body impedance is a measure of ECW, as a low-frequency current cannot penetrate the cell membrane, which acts, with its layers of protein, lipids, and proteins, as an electrical capacitor. With increasing frequencies the capacitor features of the cell membrane diminish and gradually ICW also participates in the conduc-tance of the current, resulting in lower impedance values at higher frequencies. Hence, at higher fre-quencies, TBW is measured. TBW and ECW can be predicted from impedance at high and low frequency, respectively, using empirically derived prediction for-mulae. Other parameters are often taken into consid-eration, such as body weight, age, and gender.

Most prediction equations are based on statistical relationships between empirically measured im-pedance index values (height2/impedance) and body water values obtained by dilution techniques such as deuterium oxide dilution (for TBW) and bromide dilution (for ECW). As body water in healthy subjects is an assumed fixed part (73%) of the FFM, bioelectri-cal impedance measurements can also be used for the prediction of the FFM and hence body fat percentage. For those prediction equations, the impedance index was related to measures of FFM, normally obtained by densitometry or by DXA.

Body impedance depends on the frequency of the current used and on body water distribution between the extracellular and intracellular space and between the different geometrical body compartments (legs, trunk, and arms). This calls for extreme caution in the interpretation of calculated body composition values in situations where body water distribution can be disturbed, as is the case, for example, in dialysis patients and in ascites. In general, prediction formulae based on impedance values are strongly population specific, and age and gender are important contribu-tors. Differences between populations and individuals are partly caused by differences in body build (e.g., relatively long legs), which is not surprising, as the legs contribute most to total body impedance relative to other parts of the body.

Currently available impedance analyzers vary in their electrical features and in their principles. Many companies have developed impedance analyzers for personal use, anticipating considerable interest among the public in determining their body fat per-centage. There are instruments that measure imped-ance from foot to foot while standing on a weighing scale and provide not only body weight but also body fat percentage. Other instruments measure imped-ance from hand to hand and allow the reading of body fat percentage, using a built-in software program in which weight, height, age, and gender have to be entered. Combinations of foot-to-foot and hand-to-hand impedance analyzers are also marketed.

As for all other impedance analyzers, the incorpo-rated formulae are population specific and have a prediction error of 4–5%. This means that, apart from a systematic error (prediction formula is not valid), the value can be as much as 10% off in extreme cases. This kind of error is similar to the possible error in skinfold thickness measurements, and hence impedance is no better than skinfold thickness mea-surements. The advantage of impedance analyzers is that there is no need to undress and measurements are less prone to observer bias.